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Joint Optimization of PAoI and Queue Backlog with Energy Constraints in LoRa Gateway Systems

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Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2023)

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Abstract

Peak Age of Information(PAoI), as a performance indicator representing the freshness of information, has attracted the attention of researchers in recent years. The data packet transmission rate in the LoRa network determines the information freshness level for system packets. In order to study the optimal scheduling of data packets, we try to use the PAoI to describe the real-time level of the end devices(\( EDs \)) and reduce it. We use edge servers to process monitoring data packets at the edge of the network to improve the efficiency of \( EDs \) and the information freshness level of data. Since packet transmission will be constrained by \( EDs \) battery queue energy and gateway queue backlog, we propose an optimization problem that aims to minimize the long-term average PAoI of \( EDs \) while ensuring network stability. With the Lyapunov optimization framework, the long-term stochastic optimization problem is transformed into a single-slot optimization problem. Furthermore, to avoid the problem of too large search space, we propose a dynamic strategy space reduction algorithm (SSDR) to shrink the strategy space. The simulation experiments show that our SSDR algorithm can optimize the PAoI index of \( EDs \) in various situations and satisfy the constraints of long-term optimization.

The work is supported by the Key Technology Research and Development Project of Hefei, NO. 2021GJ029.

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Authors and Affiliations

  1. School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, 230009, China

    Lei Shi, Rui Ji, Zhen Wei, Shilong Feng & Zhehao Li

  2. Engineering Research Center of Safety Critical Industrial Measurement and Control Technology, Ministry of Education, Hefei, 230009, China

    Lei Shi, Rui Ji, Zhen Wei, Shilong Feng & Zhehao Li

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  1. Lei Shi
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  3. Zhen Wei
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  4. Shilong Feng
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Correspondence to Rui Ji .

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Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. Xi’an Jiaotong-Liverpool, Suzhou, China

    Xinheng Wang

  3. University of Peloponnese, Patra, Greece

    Nikolaos Voros

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Shi, L., Ji, R., Wei, Z., Feng, S., Li, Z. (2024). Joint Optimization of PAoI and Queue Backlog with Energy Constraints in LoRa Gateway Systems. In: Gao, H., Wang, X., Voros, N. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 563. Springer, Cham. https://doi.org/10.1007/978-3-031-54531-3_15

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  • DOI: https://doi.org/10.1007/978-3-031-54531-3_15

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